Multiblock data analysis with the RGCCA package - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Journal Articles Journal of Statistical Software Year : 2023

Multiblock data analysis with the RGCCA package


Multiblock component methods aim to study the relationships between several sets of variables. Regularized Generalized Canonical Correlation Analysis (RGCCA) is a unified and flexible framework that gathers fifty years of multiblock component methods. RGCCA offers a unified implementation strategy for all these methods. This implementation is made available within the RGCCA package. In addition, the RGCCA package produces graphical outputs and statistics to assess the robustness/significance of the analysis. The usefulness of the RGCCA package is illustrated in this paper on two real datasets. The RGCCA package is freely available on the ComprehensiveR Archive Network (CRAN) and GitHub
Fichier principal
Vignette du fichier
RGCCA.pdf (242 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Licence : CC BY - Attribution

Dates and versions

hal-04094025 , version 1 (24-07-2023)





Fabien Girka, Etienne Camenen, Caroline Peltier, Arnaud Gloaguen, Vincent Guillemot, et al.. Multiblock data analysis with the RGCCA package. Journal of Statistical Software, 2023, pp.1-36. ⟨10.18637/jss.v000.i00⟩. ⟨hal-04094025⟩
30 View
3 Download



Gmail Facebook Twitter LinkedIn More